In our previous exploration of the Model Context Protocol (MCP), we discovered how it can transform file management. Today, we’re taking a deeper dive into building with MCP, whether you’re looking to create custom MCP servers, integrate them with AI clients, or master debugging tools. This comprehensive guide will equip you with everything you need to start contributing to the MCP ecosystem.
Getting Started with Cline and MCP
Cline, an autonomous coding agent for VS Code, serves as our primary tool for this tutorial. This powerful extension can edit files, run commands, and interact with browsers, always seeking permission before taking action. Here’s how to get started:
- Install Cline from the VS Code extensions marketplace
- Configure your Language Model API key (supports Anthropic or OpenRouter)
- Select your preferred model (Sonnet recommended)
- Optional: Add custom LLM instructions
Adding Existing MCP Servers
Let’s begin by adding the Brave Search MCP server to Cline. There are two approaches:
Manual Configuration
- Visit github.com/modelcontextprotocol/servers
- Locate the Brave Search MCP server configuration
- Sign up for a free Brave API key (2,000 queries/month)
- Copy the configuration and paste it into Cline’s MCP settings
- Add your API key to the configuration
Automated Installation
Alternatively, you can ask Cline to handle the installation:
- Install the @modelcontextprotocol/server-brave-search package via npm
- Use the dist folder under node_modules
- Configure the MCP server with your API key
Creating a Custom MCP Server
One of MCP’s powerful features is the ability to create custom servers. We’ll demonstrate this by building a date/time server:
- Start a new task in Cline
- Request to “add a tool to tell the current date and time”
- Choose between manual approval or auto-approve mode
- Let Cline handle file creation and configuration
This example showcases how easily we can extend MCP’s functionality with custom servers that meet specific needs.
Working with Multiple MCP Servers
The true power of MCP becomes apparent when combining multiple servers. We demonstrated this by:
- Using the custom date/time server
- Integrating the Brave Search server
- Adding the Fetch MCP server for documentation retrieval
This combination allows for powerful workflows, such as:
- Checking current dates
- Searching for latest version information
- Fetching and saving documentation
- Creating comprehensive reference materials
Debugging with MCP Inspector
MCP provides robust debugging tools, with MCP Inspector being a standout feature. To use it:
- Launch via NPX:
npx @modelcontextprotocol/inspector
npx @modelcontextprotocol/server-brave-search- Access the interface at localhost
- Configure environment variables
- Explore available features:
- Resource browsing
- Prompt template testing
- Tool examination
- Execution testing
- Log monitoring
The Inspector provides a comprehensive view of your MCP server’s capabilities and helps identify and resolve issues efficiently.
Best Practices and Tips
When working with MCP, consider these recommendations:
- Environment Variables: Always secure sensitive data like API keys
- Error Handling: Utilize both Cline’s debugging capabilities and MCP Inspector
- Auto-approve Limits: Set appropriate limits when using auto-approve mode
- Server Integration: Test thoroughly when combining multiple MCP servers
- Documentation: Keep reference materials updated for each server
Conclusion
MCP’s standardized approach to AI tool integration opens up countless possibilities for developers. Whether you’re building custom tools, creating AI integrations, or developing specialized servers, the protocol provides a robust foundation for your projects.
The combination of Cline’s natural language interface, MCP’s extensibility, and comprehensive debugging tools creates a powerful development environment. As the MCP ecosystem continues to grow, the opportunities for innovation expand with it.
Ready to start building with MCP? The resources mentioned in this guide will help you get started:
Happy coding!